bio-crispr-screens-jacks-analysis
JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens) for modeling sgRNA efficacy and gene essentiality. Use when analyzing multiple CRISPR screens simultaneously or when accounting for variable sgRNA efficiency across experiments.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-crispr-screens-jacks-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: MAGeCK 0.5+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scipy 1.12+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # JACKS CRISPR Screen Analysis **"Analyze multiple CRISPR screens jointly with JACKS"** → Model sgRNA efficacy and gene essentiality simultaneously across multiple screens, accounting for variable guide efficiency. - Python: `jacks.infer_JACKS()` for joint analysis across experiments JACKS jointly models sgRNA efficacy and gene essentiality across multiple experiments. It infers both gene-level fitness effects and sgRNA-specific efficiency. ## Installation ```bash pip install jacks # or git clone https://github.com/felicityallen/JACKS.git cd JACKS && pip install -e . ``` ## Input File Formats ### Count Data ``` # counts.txt (tab-separated) sgRNA Gene Sample1 Sample2 Sample3 Control1
- Version Compatibility
- Installation
- Input File Formats
- Count Data
- Replicate Map
- Guide-Gene Map
- Basic JACKS Analysis
- Command Line
- Python API
- Output Files
- Interpret Gene Results
- sgRNA Efficacy Analysis
- Visualization
- Gene Effect Plot
pip install jacks or git clone https://github.com/felicityallen/JACKS.git cd JACKS && pip install -e . Run JACKS python -m jacks.run_JACKS \ counts.txt \ replicatemap.txt \ guidemap.txt \ output_prefix \
What does the bio-crispr-screens-jacks-analysis skill do?
JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens) for modeling sgRNA efficacy and gene essentiality. Use when analyzing multiple CRISPR screens simultaneously or when accounting for variable sgRNA efficiency across experiments.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-crispr-screens-jacks-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.